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Using Multiple Measures to Make Math Placement Decisions: Implications for Access and Success in Community Colleges

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Abstract

Community college students are often placed in developmental math courses based on the results of a single placement test. However, concerns about accurate placement have recently led states and colleges across the country to consider using other measures to inform placement decisions. While the relationships between college outcomes and such measures as high school GPA, prior math achievement, and noncognitive measures are well-known, there is little research that examines whether using these measures for course placement improves placement decisions. We provide evidence from California, where community colleges are required to use multiple measures, and examine whether this practice increases access and success in college-level courses. Using data from the Los Angeles Community College District, we find that students who were placed into higher-level math due to multiple measures (e.g., GPA and prior math background) performed no differently from their higher scoring peers in terms of passing rates and long-term credit completion. The findings suggest that community colleges can improve placement accuracy in developmental math and increase access to higher-level courses by considering multiple measures of student preparedness in their placement rules.

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Notes

  1. The terms remedial, developmental, basic skills, and preparatory are often used interchangeably in reference to the set of courses that precede college-level courses. We prefer to use the term developmental.

  2. Details of the policy are provided in Perry et al. (2010).

  3. Unobservable factors such as easiness of grading or grade inflation at the classroom level could make it possible for boosted students to have a higher probability of passing the higher-level course than the lower-level course: P(SLCH) > P(SLCL).

  4. Unobservable factors such as diligence/effort could make it possible for the boosted students to have a greater probability of passing the high-level course than more academically-prepared students: P(SLCH) > P(SHCH).

  5. There is a “challenge” process in which students can waive pre-requisites if they provide adequate evidence of their math preparation. Our data suggest that less than 5 % of enrolled students complete this process.

  6. In College J, only 27 out of 4,303 students earned negative multiple measure points, and of those, only 2 were placed in a lower-level course as a result of point deductions.

  7. Results for other colleges are available upon request.

  8. The ACCUPLACER, for example, has different subtests such as Arithmetic or Elementary Algebra. Colleges use different subtest scores to make placement decisions.

  9. This figure includes students who took higher-level courses, which is possible if students challenge their placement and receive permission to enroll in a higher-level course, and students who chose to take lower-level courses. As a robustness check, we ran models where we included students who enrolled in courses different from those in which they were placed, as well as students who did not enroll (with zeroes assigned for unobserved outcomes), and found no significant differences in estimated coefficients.

  10. We did not examine outcomes for students boosted to college-level math since students have a range of course options available to them if they are not placed in developmental math and are allowed to take college-level math courses (e.g. pre-calculus, calculus, or statistics).

  11. In some LACCD colleges, including Colleges A and H, students who take different ACCUPLACER or MDTP subtests may end up being placed in the same course level.

  12. We thank the anonymous reviewers for this suggestion.

  13. For example, both Colleges D and E assign students to what we call “extended” algebra courses, which extends the developmental math sequence by an additional semester.

  14. We acknowledge that this assumption would be less likely to hold in a college where a larger percentage of students receive a multiple measure boost, such as College J.

  15. Analyses by level of developmental math for all colleges are available from the authors upon request.

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Authors and Affiliations

  1. Rossier School of Education, University of Southern California, 3470 Trousdale Parkway, Waite Phillips Hall WPH 503C, Los Angeles, CA, 90089, USA

    Federick Ngo & William W. Kwon

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  1. Federick Ngo
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  2. William W. Kwon
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Correspondence to Federick Ngo.

Appendix

Appendix

See Tables 7, 8 and 9

Table 7 Probability of passing placed math course, pooled regression results
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Table 8 Regression results by math level for multiple measure boost based on prior math achievement, College A
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Table 9 Regression results by math level for multiple measure boost based on HSGPA, College H
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Ngo, F., Kwon, W.W. Using Multiple Measures to Make Math Placement Decisions: Implications for Access and Success in Community Colleges. Res High Educ 56, 442–470 (2015). https://doi.org/10.1007/s11162-014-9352-9

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